Title :
Automatic detecting actomyosin complex biological particles in cryo-EM images
Author :
Yang, Jianfei ; Ohashi, Takaya ; Yasunaga, T.
Author_Institution :
Dept. of Comput. Sci. & Syst. Eng., Kyushu Inst. of Technol., Fukuoka, Japan
Abstract :
This paper describes how actomyosin complex particles are detected automatically. We propose a new approach that combines both gray level co-occurrence matrix to extract texture features and the SVM classifier to detect actomyosin complex particles automatically. Experimental results show that detection rate achieves 94.81%, the false positive rate is 2.79%, and the false negative rate is 5.46%.
Keywords :
biothermics; feature extraction; image texture; matrix algebra; medical diagnostic computing; medical expert systems; pattern classification; support vector machines; SVM classifier; actomyosin complex biological particles; automatic detection; cryo-EM images; gray level co-occurrence matrix; texture feature extraction; Artificial neural networks; Biology; Feature extraction; Image analysis; Image reconstruction; Image texture analysis; Support vector machine classification; Support vector machines; Symmetric matrices; Systems engineering and theory;
Conference_Titel :
Communications, Circuits and Systems, 2005. Proceedings. 2005 International Conference on
Print_ISBN :
0-7803-9015-6
DOI :
10.1109/ICCCAS.2005.1495258
